"The model generated totally different output every time you ran it, even with fixed seeds." - I remember seeing code takedowns of the model from anti-lockdown people who repeatedly cite this issue.
But there is a valid reason for this to happen, and it doesn't mean bugs in the code. If the code is run in a distributed way (multiple threads, processes or machines), which it was, the order of execution is never guaranteed. So even setting the seed will produce a different set of results if the outcomes of each separate instance depend on each other further in the computation.
There are ways to mitigate this, depending on the situation and the amount of slowdown that's acceptable. Since this model was collecting outcomes to create a statistical distribution, rather than a single deterministic number, it didn't need to.
The fact the model was also drawing distributions also will be why different runs produced possibly vastly different results. Those results would be at different ends of a distribution. Only distributions are sampled and used, not single numbers.
Regarding the GCSE level comment, my concern was the opposite, that the model was trying to model too much, and that inaccuracies would build up. No model is perfect (including this one) and the more assumptions made the larger the room for error. But they validated the model with some simpler models as a sanity check.
My view on criticisms of the model were that they were more politically motivated, and the code takedowns were done by people who may have been good coders, but didn't know enough about statistical modeling.
Here's John Cormack's take on the model, he saw and cleaned up the original version before it was released.
https://mobile.twitter.com/id_aa_carmack/status/125487236876...